MACHINE LEARNING AND KEYWORD-MATCHING INTEGRATED PROTOCOL IDENTIFICATION

摘要：

Identifying the underlying protocol carried in the data traffic (i.e., Protocol Identification) is of fundamental important to QoS, Security, Network management and many other purposes. Port-based, content-based and behaviorbased are commonly used identification methods in today’s networks. However, all of these methods have their own shortcomings. In this paper, a new MAchine Learning and Keyword-matching Integrated (MALKI) protocol identification method is proposed to overcome the shortcomings brought by these existing methods. The proposed method combines the content and behaviorbased technologies together to identify the underlying protocol in the data flow. A prototype is implemented on a high performance multi-core processor platform. From the experimental results, we can see the proposed method is effective and efficient when applied into the protocol identification.

作者: Xuejun Cai Ruoyuan Zhang Bin Wang

作者单位: Ercisson, China Nokia Siemens Networks, China

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

会议地点: 北京

会议语种:英文

页码: 164-169

在线出版日期: 2010-10-26（万方平台首次上网日期，不代表论文的发表时间）